2026 The 10th International Conference on Computing and Data Analysis (ICCDA 2026)
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About this event
The 10th International Conference on Computing and Data Analysis (ICCDA 2026)
December 18–20, 2026 | Phuket, Thailand
About ICCDA 2026
The International Conference on Computing and Data Analysis (ICCDA) is an annual international forum for academia and industries to exchange visions and ideas on the state of the art and practice of computing and data analysis. ICCDA 2026, the 10th edition of this conference, will be held in Phuket, Thailand, from December 18 to 20, 2026. The event is co-sponsored by Rajamangala University of Technology Srivijaya, Thailand, and the University of Thessaly, Greece.
The conference aims to present the most rigorous and innovative research in computing and data analysis through a highly selective review process. Participants are invited to submit original research papers addressing theoretical, empirical, and applied aspects of the field.
Key Dates
- Paper Submission Deadline: July 15, 2026
- Notification of Acceptance: August 15, 2026
- Registration Deadline: August 30, 2026
- Conference Dates: December 18–20, 2026
Call for Papers
ICCDA 2026 invites submissions on topics including but not limited to:
- Mathematical, probabilistic, and statistical models and theories
- Machine learning theories, models, and systems
- Knowledge discovery theories, models, and systems
- Deep learning and scalable analysis
- Data pre-processing, reduction, and visualization
- Cloud architectures, large-scale databases, and high-performance computing
- Human-machine interaction, crowdsourcing, and collective intelligence
- Multimedia, text, and network mining and learning
- Big data analytics, optimization, and semantics
Submission Guidelines:
- Papers must be at least 5 pages (two-column format).
- Papers exceeding 6 pages will incur a $60 fee per extra page.
- Submissions must be in English and follow the provided template.
- Original work only; no concurrent submissions elsewhere.
- Submit via the online system.
Conference Proceedings
Full papers accepted after registration will be published in the ICCDA Conference Proceedings. Selected high-quality papers may also be considered for publication in partner journals (details to follow).
Awards
- Outstanding Organization Award
- Outstanding Contribution Award
- Best Paper Award
- Best Oral Presentation Award
- Best Poster Presentation Award
Contact
For general inquiries, contact Ms. Tessa Chen at iccda_Conf@yeah.net.
Data sheet
2026 The 10th International Conference on Computing and Data Analysis (ICCDA 2026) – Event Attendee & Buyer Profile Analysis
Event date: December 18–20, 2026
Location: Phuket, Thailand
Event status: Upcoming
Research date: June 29, 2026
Event Overview
| Event Name | 2026 The 10th International Conference on Computing and Data Analysis (ICCDA 2026) |
| Event Date | December 18–20, 2026 |
| Event Status | Upcoming |
| Venue | Specific venue not publicly confirmed in the official website text provided; Phuket location confirmed. |
| City | Phuket |
| State / Region | Phuket Province |
| Country | Thailand |
| Organizer | Official organizer name not clearly stated in the provided website text; conference is co-sponsored by Rajamangala University of Technology Srivijaya, Thailand and the University of Thessaly, Greece. |
| Official Event Website | iccda.org |
| Event Type | International academic and industry conference / call-for-papers event |
| Primary Category | IT & Technology |
| Secondary Applicable Categories | Science & Research; Education & Training |
| Audience Reach | Global academic and professional reach |
| Estimated Attendance / Expected Footfall | Attendance figure not publicly confirmed by the organizer. |
| Attendance Data Reliability | Low for volume metrics; high for dates, location, conference theme, and submission deadlines based on official website text. |
| Main Purpose of Event | To present peer-reviewed research and facilitate exchange between academia and industry in computing and data analysis, including machine learning, data science architecture, search, visualization, analytics, and high-performance computing. |
About the Event
ICCDA 2026 is the 10th edition of the International Conference on Computing and Data Analysis, positioned as an annual international forum for researchers and industry participants working across computing, machine learning, data analytics, knowledge discovery, cloud architectures, visualization, and related technical domains. The official website confirms the 2026 edition will take place in Phuket, Thailand, on December 18–20, 2026, and notes co-sponsorship by Rajamangala University of Technology Srivijaya and the University of Thessaly.
From a commercial intelligence perspective, this is not a broad trade-show buying event; it is a specialist conference with strong relevance for academic partnerships, applied research collaboration, technical software outreach, analytics tooling, cloud and data infrastructure engagement, and thought-leadership positioning. The most relevant participants are likely to be university researchers, technical faculty, graduate researchers, data scientists, AI/ML practitioners, and selected industry delegates involved in computing and analytics innovation.
1. Who Attends: Buyers / Attendees
| Buyer / Attendee Segment | Typical Organizations | Buying Role or Influence | Relevance to Exhibitors / Suppliers |
|---|---|---|---|
| University faculty and principal investigators | Universities, engineering schools, research institutes | Influence software, lab tools, cloud credits, datasets, and collaboration decisions | High relevance for research software, data platforms, HPC, academic publishing, and grants partnerships |
| Data scientists and machine learning researchers | Academic labs, corporate R&D teams, analytics groups | Technical evaluators and end users of analytics, ML, and visualization tools | High relevance for demos, trials, technical workshops, API-led solutions, and compute services |
| Graduate and doctoral researchers | Universities and research centers | Strong user influence, limited direct procurement authority | Useful for user adoption, paper submissions, future evangelists, and academic community penetration |
| Industry R&D and innovation teams | Software firms, AI labs, enterprise analytics teams | Assess technical fit, partnerships, and proof-of-concept opportunities | Good relevance for advanced analytics products, model development platforms, and compute infrastructure |
| Research administrators and academic program leaders | Universities, faculties, academic departments | Can influence event participation, institutional partnerships, and budget allocation | Relevant for education services, research partnerships, conference sponsorship, and institutional software programs |
| Cloud, data infrastructure, and platform architects | Data science groups, computing centers, enterprise IT teams | Evaluate technical architecture, deployment models, and compute needs | Strong fit for cloud providers, storage, data engineering tools, and performance optimization vendors |
| Conference organizers, committee members, and peer reviewers | Universities, scholarly networks, conference committees | Influence speaker placements, sponsorship visibility, and ecosystem partnerships | Relevant for sponsorship sales, publication services, and academic network development |
2. Event Location and Attendee Geographic Origin
| Geographic Area | Likely Attendee Origin | Buyer Concentration | Notes |
|---|---|---|---|
| Phuket | Local host-city delegates, local universities, and support organizations | Low to Medium | Host location is confirmed; specific venue is not publicly confirmed in the provided text. |
| Phuket Province / Southern Thailand | Regional academic and technical attendees | Medium | Likely regional draw for Thai higher-education and technical communities. |
| Thailand | National researchers, faculty, postgraduate students, and industry participants | High | Co-sponsorship by a Thai university supports strong domestic participation likelihood. |
| Asia-Pacific | Researchers and professionals from nearby regional markets | Medium to High | Conference positioning and call-for-papers format indicate cross-border academic participation. |
| Europe | Academic delegates, especially those linked to sponsor and committee networks | Medium | University of Thessaly co-sponsorship supports European academic reach. |
| Global | International paper authors, presenters, and academic collaborators | Medium | Official website frames ICCDA as an international annual conference. |
3. Audience Reach
| Reach Level | Assessment | Explanation |
|---|---|---|
| Global | Primary classification | The event is explicitly positioned as an international conference, with global paper submissions and cross-country co-sponsorship. |
| National / Regional | Secondary practical reach | Physical attendance is still likely to skew toward Thailand and broader Asia-Pacific due to travel practicality and host geography. |
4. Sample Buyer Companies and Websites
| Buyer Company / Organization | Buyer Type | Why It Is Relevant | Website | Best Job Titles to Target | Evidence Level |
|---|---|---|---|---|---|
| Rajamangala University of Technology Srivijaya | Academic co-sponsor | Official co-sponsor; relevant for research collaboration, conference participation, and academic technology outreach. | ruts.ac.th | Dean, Head of Computer Science, Research Director, IT Director, Faculty Lead | Confirmed Current-Year Participant |
| University of Thessaly | Academic co-sponsor | Official co-sponsor; relevant for international academic collaboration and research outreach. | uth.gr | Professor, Research Director, Lab Director, Department Chair, Data Science Lead | Confirmed Current-Year Participant |
Only officially confirmed current-year organizations identifiable from the provided primary source are included. No current-year attendee, speaker-organization, exhibitor, or sponsor directory was available in the source text provided.
5. Job Profiles, Industries and Event Type
| Priority | Job Title / Function | Department | Seniority Level | Why This Role Matters |
|---|---|---|---|---|
| 1 | Professor / Principal Investigator | Research / Academic | Senior / Director | Key research decision-maker and collaboration gatekeeper. |
| 2 | Research Director | Research & Development | Director | Influences platform adoption, grants alignment, and partnerships. |
| 3 | Head of Department / Department Chair | Academic Administration | Director / VP | Relevant for institutional engagement and budget-linked approvals. |
| 4 | Data Scientist | Analytics / Research | Manager / Individual Contributor | Core user of analytics, ML, and data tooling. |
| 5 | Machine Learning Engineer | Engineering / AI | Manager / Individual Contributor | Important for technical evaluation of model and compute platforms. |
| 6 | IT Director | Information Technology | Director | Relevant for infrastructure, deployment, cybersecurity, and cloud decisions. |
| 7 | CTO / Chief Digital Officer | Executive / Technology | C-Level | Relevant on the industry side for strategic research and innovation partnerships. |
| 8 | Lab Director / HPC Center Lead | Research Computing | Director | High relevance for high-performance computing and data infrastructure. |
| 9 | Program Manager | Research Programs / Partnerships | Manager | Useful for sponsored research, conference participation, and consortium activities. |
| 10 | Business Development Director | Partnerships / Commercial | Director | Relevant for industry-academia collaboration and solution partnerships. |
| Priority | Apollo Industry | Why It Fits the Event | Best Buyer Use Case |
|---|---|---|---|
| 1 | Higher Education | Core attendee base for academic conferences and paper submissions. | University faculty, labs, and computing departments. |
| 2 | Research | Strong fit for technical and scientific research organizations. | Applied research institutes and innovation centers. |
| 3 | Information Technology & Services | Broad industry participation channel for data and computing solutions. | IT consultancies, platform providers, and analytics service firms. |
| 4 | Computer Software | Highly aligned with ML, analytics, search, and data tooling. | Software vendors, MLOps, BI, and analytics platforms. |
| 5 | Computer Hardware | Relevant for compute acceleration, GPU, storage, and HPC infrastructure. | Research computing and performance-intensive environments. |
| 6 | Computer Networking | Supports data movement, distributed computing, and infrastructure scaling. | Campus networks and distributed research environments. |
| 7 | Electrical/Electronic Manufacturing | Relevant where computing research overlaps with embedded and technical systems. | Technical innovation and applied analytics environments. |
| 8 | Internet | Aligned to web mining, search, recommendation, and online behavior analytics. | Data product and recommendation system teams. |
| 9 | Semiconductors | Relevant for compute-intensive AI and system performance themes. | Hardware-enabled AI and computational optimization. |
| 10 | Telecommunications | Useful where network analytics, streaming data, and scale are relevant. | Large-scale data analysis and optimization use cases. |
| 11 | Industrial Automation | Potential fit for applied analytics and optimization research. | Predictive analytics and system performance modeling. |
| 12 | Education Management | Institutional decision-makers may sit in education administration structures. | Academic administration, digital research support, and institutional systems. |
6. Estimated Attendance
| Metric | Figure | Status | Source / Basis | Notes |
|---|---|---|---|---|
| Estimated total footfall | Attendance figure not publicly confirmed by the organizer. | Not Confirmed | Official website text reviewed | No visitor or delegate volume published in the provided primary source. |
| Exhibitor count | Not publicly confirmed | Not Confirmed | Official website text reviewed | Conference format appears paper- and program-led rather than exhibition-led. |
| Buyer count | Not publicly confirmed | Not Confirmed | Official website text reviewed | Event is more technical and research-focused than procurement-focused. |
| Speaker count | Not publicly confirmed in the source text provided | Not Confirmed | Official navigation references keynote and invited speakers | Speaker organizations may exist on the live site, but were not included in the provided source text. |
| Sponsor count | 2 co-sponsoring institutions confirmed | Confirmed | Official website text | Rajamangala University of Technology Srivijaya and University of Thessaly. |
| Historical attendance | No numeric historical attendance data confirmed | Historical / prior-year evidence unavailable | Provided source text lists previous editions only | No prior-year volume metrics included in the source text. |
7. Key Focus Areas and Buyer Engagement
| Focus Area | Typical Buyer Need | Buyer Engagement Opportunity | Relevant Supplier Offering |
|---|---|---|---|
| Machine learning and deep learning | Model development, experimentation, optimization | Technical demos, research credits, pilot programs | ML platforms, notebooks, MLOps, compute services |
| Knowledge discovery and data mining | Pattern extraction, analytics workflows, scalable mining | Use-case workshops and applied research collaborations | Analytics software, graph mining tools, data preparation solutions |
| High performance computing for data analytics | Processing scale, speed, infrastructure efficiency | Infrastructure evaluation and benchmark discussion | HPC hardware, GPU servers, storage, parallel compute environments |
| Data architectures and warehouses | Scalable storage, cloud integration, governance | Architecture consulting and proof-of-concept discussions | Cloud data platforms, warehouses, ETL, orchestration tools |
| Search, recommendation, and semantic retrieval | Information retrieval, personalization, user relevance | Applied AI discussion with research and product teams | Search engines, recommendation frameworks, vector and semantic tools |
| Big data visualization and analytics | Insight communication, dashboarding, visual exploration | Hands-on demonstrations and academic licensing offers | BI tools, visual analytics platforms, data storytelling solutions |
| Cloud computing and service data analysis | Elastic compute, collaboration, deployment speed | Cloud credit programs, academic alliance partnerships | Cloud IaaS/PaaS, managed notebooks, storage and compute clusters |
| Human-machine interaction and interfaces | Usability, interaction design, applied intelligence | Research showcase and collaboration opportunities | UX analytics, interactive systems, experimentation platforms |
Lead Quality Assessment
| Factor | Assessment | Explanation |
|---|---|---|
| Buyer relevance | Medium | Strong for academic technology, cloud, analytics, and research tools; weaker for general procurement-oriented selling. |
| Decision-maker availability | Medium | Senior faculty and research leaders are relevant, but direct commercial purchasing authority may be distributed. |
| Data collection potential | Low to Medium | Public attendee volume and participant directory data are limited in the source reviewed. |
| Apollo targeting potential | High | Relevant audiences can be targeted effectively by industry, department, title, and research/analytics keywords. |
| Geographic targeting potential | High | Thailand, Asia-Pacific, and international academic hubs can be segmented cleanly. |
| Best outreach approach | High | Thought leadership, research collaboration, academic licensing, and technical demonstration messaging will perform better than direct sales language. |
| Overall lead quality | Medium | Good niche event for highly technical outreach; not ideal for broad buyer-list monetization without more participant data. |
| Best use case | High | Ideal for academic partnerships, data/AI software prospecting, cloud credits, and research infrastructure solutions. |
| Limitations / risks | Medium | Limited public attendee confirmation, probable smaller scale than mass trade shows, and mixed commercial authority among attendees. |
Suitability for B2B attendee list building: Moderate only. Better suited for targeted niche account development than large-volume event list sales, unless a fuller attendee or speaker directory becomes available later.
Apollo.io Targeting Recommendation
| Filter Type | Recommended Filters | Purpose |
|---|---|---|
| Apollo industries | Higher Education; Research; Information Technology & Services; Computer Software; Computer Hardware; Internet; Telecommunications; Education Management | Capture both academic and applied-industry segments relevant to computing and analytics. |
| Departments | Research; Engineering; Information Technology; Education; Operations; Business Development | Focus on research, technical, and institutional partnership functions. |
| Seniority | C-Level; VP; Director; Head; Manager; Professor-equivalent where available | Prioritize decision-makers and budget influencers. |
| Job titles | Professor, Principal Investigator, Research Director, Department Chair, Head of Data Science, Data Scientist, Machine Learning Engineer, CTO, IT Director, Lab Director, HPC Manager, Program Manager | Map to conference themes and likely attendee roles. |
| Geography | Thailand; Southeast Asia; Asia-Pacific; Greece; selected global university clusters | Align with host market plus co-sponsor and international research reach. |
| Employee size | 51–200; 201–500; 501–1,000; 1,001–5,000; 5,001+ | Useful for targeting universities, institutes, and mature software organizations. |
| Keywords | machine learning, deep learning, data analysis, knowledge discovery, data science, big data, visualization, high performance computing, semantic search, recommendation systems, cloud computing | Find technical teams most aligned with ICCDA topics. |
| Technologies | Cloud platforms, AI/ML stack, analytics tools, HPC-related infrastructure where available | Useful for technical solution vendors and infrastructure targeting. |
| Revenue range | Optional; mid-market to enterprise for industry accounts | Helps separate enterprise technology buyers from smaller labs. |
| Company type | Universities, research institutes, software companies, technical R&D groups | Matches the conference’s academic-industry blend. |
Suggested Apollo Search Logic: ("machine learning" OR "data analysis" OR "data science" OR "deep learning" OR "knowledge discovery" OR "big data" OR "high performance computing" OR "semantic search" OR "recommendation systems") AND (Professor OR "Research Director" OR "Data Scientist" OR "Machine Learning Engineer" OR "IT Director" OR CTO OR "Lab Director").
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Sources & Verification Notes
| Source | Type | What It Verified | Reliability |
|---|---|---|---|
| ICCDA 2026 Official Website | Official event website | Confirmed event name, official dates, host city, host country, conference theme, co-sponsors, important deadlines, and technical topic areas. | High |
| ICCDA 2026 Submission System | Official linked submission page | Supports that the event is active as a call-for-papers conference. | Medium to High |
| Provided official website content in user brief | Primary-source extract | Used as the primary source of truth where direct site browsing details were not separately expanded. | High |
Verification note: The user’s “known details” included January 16–18, 2026 and “Venue: Phuket,” but the official event website text clearly states December 18–20, 2026 in Phuket, Thailand. This report follows the official website as the primary source of truth. Specific hotel or convention venue details were not visible in the provided official text and therefore are not asserted as confirmed.
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